We propose a framework for large scale learning and annotation of structured models. The system interleaves interactive labeling (where the current model is used to semiautomate t...
In this paper, we present a novel, threshold-free robust estimation framework capable of efficiently fitting models to contaminated data. While RANSAC and its many variants have...
Parameter tampering attacks are dangerous to a web application whose server fails to replicate the validation of user-supplied data that is performed by the client. Malicious user...
Large-scale network monitoring systems require efficient storage and consolidation of measurement data. Relational databases and popular tools such as the Round-Robin Database sho...
The Route Shepherd tool demonstrates applications of choosing between routing protocol configurations on the basis of rigorouslysupported theory. Splitting the configuration spa...
Alexander J. T. Gurney, Xianglong Han, Yang Li, Bo...